• Designs and builds scalable data extracts, integrations, transformations, and data models. • Ensures successful deployment and provisioning of data solutions across required environments. • Designs and implements data architectures and applications that enable speed, quality, and operational efficiency. • Interacts with cross-functional stakeholders to gather and define requirements and translate them into technical designs. • Develops deep familiarity with enterprise datasets, builds domain knowledge, and advances data quality. • Reviews requirements, identifies gaps, and drives resolution with stakeholders. • Identifies and recommends continuous improvement opportunities, ensuring integrations are automated, governed, and observable. • Serves as a key team member in designing and deploying a ground-up cloud data platform and pipeline. • Partners with data scientists to design, build, and maintain reproducible machine-learning pipelines. • Implements CI/CD for data and ML workflows. • Builds and maintains production-grade ML infrastructure such as feature stores, model registries, and data versioning. • Ensures ML models follow best-practice governance, including automated model performance monitoring and alerting. • Designs scalable data pipelines optimized for ML workloads. • Establishes MLOps standards, coding practices, and automation patterns that scale across teams.